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CHANGELOG.md

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Changelog

All notable changes to this project will be documented in this file.

[unreleased]

[v1.5.0]

New features

Enhancements

Bug fixes

Known issues

  • OpenVINO(==2023.0) IR inference is not working well on 2-stage models (e.g. Mask-RCNN) exported from torch>=1.13.1
  • NNCF QAT optimization is disabled for MaskRCNN models due to CUDA runtime error in ROIAlign kernel on torch==2.0.1

[v1.4.4]

Enhancements

Bug fixes

[v1.4.3]

Enhancements

[v1.4.2]

Enhancements

Bug fixes

[v1.4.1]

Enhancements

Bug fixes

[v1.4.0]

New features

Enhancements

Bug fixes

Known issues

  • OpenVINO(==2023.0) IR inference is not working well on 2-stage models (e.g. Mask-RCNN) exported from torch==1.13.1

[v1.3.1]

Enhancements

  • n/a

Bug fixes

Known issues

  • OpenVINO(==2022.3) IR inference is not working well on 2-stage models (e.g. Mask-RCNN) exported from torch==1.13.1 (working well up to torch==1.12.1) (open-edge-platform#1906)

[v1.3.0]

New features

Enhancements

Bug fixes

Known issues

  • OpenVINO(==2022.3) IR inference is not working well on 2-stage models (e.g. Mask-RCNN) exported from torch==1.13.1 (working well up to torch==1.12.1) (open-edge-platform#1906)

[v1.2.3]

Bug fixes

  • Return raw anomaly map instead of colormap as metadata to prevent applying colormap conversion twice (open-edge-platform#2217)
  • Hotfix: use 0 confidence threshold when computing best threshold based on F1

[v1.2.2]

Enhancements

  • Improve warning message for tiling configurable parameter

Known issues

  • OpenVINO(==2022.3) IR inference is not working well on 2-stage models (e.g. Mask-RCNN) exported from torch==1.13.1 (working well up to torch==1.12.1) (open-edge-platform#1906)

[v1.2.1]

Enhancements

Bug fixes

[v1.2.0]

New features

Enhancements

Bug fixes

Known issues

  • OpenVINO(==2022.3) IR inference is not working well on 2-stage models (e.g. Mask-RCNN) exported from torch==1.13.1 (working well up to torch==1.12.1) (open-edge-platform#1906)

[v1.1.2]

Bug fixes

[v1.1.1]

Bug fixes

  • Add missing OpenVINO dependency in exportable code requirement

[v1.1.0]

New features

Enhancements

Bug fixes

Known issues

  • OpenVINO(==2022.3) IR inference is not working well on 2-stage models (e.g. Mask-RCNN) exported from torch==1.13.1 (working well up to torch==1.12.1) (open-edge-platform#1906)

[v1.0.1]

Enhancements

  • Refine documents by proof review
  • Separate installation for each tasks
  • Improve POT efficiency by setting stat_requests_number parameter to 1
  • Introduce new tile classifier to enhance tiling inference performance in MaskRCNN.

Bug fixes

  • Fix missing classes in cls checkpoint
  • Fix action task sample codes
  • Fix label_scheme mismatch in classification
  • Fix training error when batch size is 1
  • Fix hang issue when tracing a stack in certain scenario
  • Fix pickling error by Removing mmcv cfg dump in ckpt

[v1.0.0]

NOTES

OpenVINO™ Training Extensions which version 1.0.0 has been updated to include functional and security updates. Users should update to the latest version.

New features

  • Adaptation of Datumaro component as a dataset interface
  • Integrate hyper-parameter optimizations
  • Support action recognition task
  • Self-supervised learning mode for representational training
  • Semi-supervised learning mode for better model quality

Enhancements

  • Installation via PyPI package
  • Enhance find command to find configurations of supported tasks / algorithms / models / backbones
  • Introduce build command to customize task or model configurations in isolated workspace
  • Auto-config feature to automatically select the right algorithm and default model for the train & build command by detecting the task type of given input dataset
  • Improve documentation
  • Improve training performance by introducing enhanced loss for the few-shot transfer

Bug fixes

  • Fixing configuration loading issue from the meta data of the model in OpenVINO task for the backward compatibility
  • Fixing some minor issues

[v0.5.0]

NOTES

OpenVINO Training Extension which version is equal or older then v0.5.0 does not include the latest functional and security updates. OTE Version 1.0.0 is targeted to be released in February 2023 and will include additional functional and security updates. Customers should update to the latest version as it becomes available.

Added

Changed

Fixed

[v0.4.0]

Added

Fixed

[v0.3.1]

Fixed

  • Neural Network Compression Framework (NNCF)

  • Model Preparation Algorithm (MPA)

Security

[v0.3.0]

Added

Changed

Fixed

[v0.2.0]

Added

  • Model Preparation Algorithm (MPA), a newly introduced OTE Algorithm backend for advanced transfer learning
    • Class-Incremental Learning support for OTE models
      • Image Classification
      • Object Detection
      • Semantic Segmentation
  • Object counting & Rotated object detection are added to Object Detection backend
  • Increased support for NNCF / FP16 / HPO
  • Ignored label support
  • Stop training on NaN losses

Changed

  • Major refactoring
    • Tasks & model templates had been moved to OTE repo from each OTE Algorithm backend

[v0.1.1]

Fixed

  • Some minor issues

[v0.1.0]

Added

  • OTE SDK, defines an interface which can be used by OTE CLI to access OTE Algorithms.
  • OTE CLI, contains set of commands needed to operate with deep learning models using OTE SDK Task interfaces.
  • OTE Algorithms, contains sub-projects implementing OTE SDK Task interfaces for different deep learning models.
    • Anomaly Classification
    • Image Classification
    • Object Detection
    • Semantic Segmentation